Graph Feature Generation based on Scene Graph Benchmark Application on Video
Jiyoun Lim, NamKyung Lee · 2022 13th International Conference on Information and Communication Technology Convergence (ICTC) · 2022
In the field of vision research, it is considered that the analysis of scene graphs can help machines comprehend higher-level visual scene contexts. The data structure that both detects objects and defines their relationships is called a scene graph. The scene graph has been applied to diverse tasks, including action recognition, image captioning and visual question answering. It is also suggested as a method for understanding the video context. The amount of video data needed for training to produce a scene graph is nonetheless insufficient. Therefore, the inference model was applied to real-world data, and the possibility of usage of scene graph as a visual feature was identified.